Cover Image

The Partially Observable Off-Switch Game

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Garber, Andrew, Subramani, Rohan, Luu, Linus, Bedaywi, Mark, Russell, Stuart, Emmons, Scott
Format:	Preprint
Published:	2024
Subjects:	Computer Science and Game Theory Artificial Intelligence Multiagent Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Observation Interference in Partially Observable Assistance Games
by: Emmons, Scott, et al.
Published: (2024)

Online Competitive Information Gathering for Partially Observable Trajectory Games
by: Krusniak, Mel, et al.
Published: (2025)

Characterising Interventions in Causal Games
by: Mishra, Manuj, et al.
Published: (2024)

Cooperation and Control in Delegation Games
by: Sourbut, Oliver, et al.
Published: (2024)

Approximate State Abstraction for Markov Games
by: Ishibashi, Hiroki, et al.
Published: (2024)

Expectation vs. Reality: Towards Verification of Psychological Games
by: Kwiatkowska, Marta, et al.
Published: (2024)

Observable Perfect Equilibrium
by: Ganzfried, Sam
Published: (2022)

Regret Minimization in Population Network Games: Vanishing Heterogeneity and Convergence to Equilibria
by: Hu, Die, et al.
Published: (2025)

Self-adaptive PSRO: Towards an Automatic Population-based Game Solver
by: Li, Pengdeng, et al.
Published: (2024)

A Computable Game-Theoretic Framework for Multi-Agent Theory of Mind
by: Zhu, Fengming, et al.
Published: (2025)

Learning in Multi-Objective Public Goods Games with Non-Linear Utilities
by: Orzan, Nicole, et al.
Published: (2024)

Quadratic Programming Approach for Nash Equilibrium Computation in Multiplayer Imperfect-Information Games
by: Ganzfried, Sam
Published: (2025)

Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning
by: Gemp, Ian, et al.
Published: (2024)

Simulation-Free PSRO: Removing Game Simulation from Policy Space Response Oracles
by: Liu, Yingzhuo, et al.
Published: (2025)

Game Theory and Multi-Agent Reinforcement Learning : From Nash Equilibria to Evolutionary Dynamics
by: De La Fuente, Neil, et al.
Published: (2024)

Independent Learning of Nash Equilibria in Partially Observable Markov Potential Games with Decoupled Dynamics
by: Jordan, Philip, et al.
Published: (2026)

Differentiable Bilevel Programming for Stackelberg Congestion Games
by: Li, Jiayang, et al.
Published: (2022)

Environment Complexity and Nash Equilibria in a Sequential Social Dilemma
by: Yasir, Mustafa, et al.
Published: (2024)

From Natural Language to Extensive-Form Game Representations
by: Deng, Shilong, et al.
Published: (2025)

MR-LDM -- The Merge-Reactive Longitudinal Decision Model: Game Theoretic Human Decision Modeling for Interactive Sim Agents
by: Holley, Dustin, et al.
Published: (2025)

Data-Augmented Game Starts for Accelerating Self-Play Exploration in Imperfect Information Games
by: Lanier, JB, et al.
Published: (2026)

Dominated Actions in Imperfect-Information Games
by: Ganzfried, Sam
Published: (2025)

Facility Location Games with Scaling Effects
by: He, Yu, et al.
Published: (2024)

Evaluating LLMs in Open-Source Games
by: Sistla, Swadesh, et al.
Published: (2025)

Offline Fictitious Self-Play for Competitive Games
by: Chen, Jingxiao, et al.
Published: (2024)

Opponent Modeling in Multiplayer Imperfect-Information Games
by: Ganzfried, Sam, et al.
Published: (2022)

Consistent Opponent Modeling in Imperfect-Information Games
by: Ganzfried, Sam
Published: (2025)

Bounded Rationality Equilibrium Learning in Mean Field Games
by: Eich, Yannick, et al.
Published: (2024)

Learning Optimal Tax Design in Nonatomic Congestion Games
by: Cui, Qiwen, et al.
Published: (2024)

Online Learning of Counter Categories and Ratings in PvP Games
by: Lin, Chiu-Chou, et al.
Published: (2025)

Strategic Algorithmic Monoculture: Experimental Evidence from Coordination Games
by: Ballestero, Gonzalo, et al.
Published: (2026)

RuleSmith: Multi-Agent LLMs for Automated Game Balancing
by: Zeng, Ziyao, et al.
Published: (2026)

Inverse Concave-Utility Reinforcement Learning is Inverse Game Theory
by: Çelikok, Mustafa Mert, et al.
Published: (2024)

Partially Observable Multi-Agent Reinforcement Learning with Information Sharing
by: Liu, Xiangyu, et al.
Published: (2023)

Scalable Mechanism Design for Multi-Agent Path Finding
by: Friedrich, Paul, et al.
Published: (2024)

Learning in Strategic Queuing Systems with Small Buffers
by: Abel, Ariana, et al.
Published: (2025)

The Hive Mind is a Single Reinforcement Learning Agent
by: Soma, Karthik, et al.
Published: (2024)

Emergent Cooperation under Uncertain Incentive Alignment
by: Orzan, Nicole, et al.
Published: (2024)

What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
by: Han, Songyang, et al.
Published: (2022)

On multiagent online problems with predictions
by: Istrate, Gabriel, et al.
Published: (2025)